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Adding artificial intelligence (AI) tools to existing networks, systems and infrastructures may seem like a smart move, but a new EY white paper says that at least three things have to happen for those investments to pay off. In other words, simply “adding more AI” doesn’t always produce the desired results—especially when the underlying legacy infrastructure can’t support it.
“As organizations approach AI transformation, too many attempt to simply add new technologies to their existing but quickly aging workflows and technology environments,” EY points out in “Why business readiness is critical for supply chain AI.”
“This kind of bolt-on approach means two things,” it continues. “The promise of AI in reshaping supply chain efficiencies and outputs will never be truly realized, and those organizations that take a more holistic, business-ready approach will be the ones that win in the emerging age of AI-driven supply chain operations.”
All-in on AI
Right now, EY says nearly three-quarters of organizations plan to deploy generative AI (GenAI) technologies in their supply chains and 80% think that will help reinvent their operations. Nearly as many companies (70%), say failing to integrate GenAI will leave them at a competitive disadvantage. As companies weave more AI into their supply chains, legacy systems have become a common roadblock that caps the technology’s full potential. In its new white paper, “The importance of business and process readiness for supply chain technology and AI implementations,” EY discusses the problems that arise when companies try to layer new technologies on top of outdated workflows. It also offers solutions to the problem across three business areas.
“Digital technologies thrive in environments where data flows freely between functions; decisions are made in real time or near real time; and automation is trusted within clearly defined boundaries,” it says. “If these conditions do not exist, technology remains a bolt-on enhancement rather than a transformative capability.”
For example, if planning processes still rely on weekly batch cycles and manual approvals, even the most advanced AI-driven forecasting tool will be underutilized. To avoid this problem, EY recommends taking these steps across three areas:
Processes and Governance
1. Review end-to-end processes, including those directly and indirectly impacted by new technology. New solutions will affect upstream and downstream activities, so processes must be connected across the supply chain.
2. Simplify decision-making by removing unnecessary handoffs or approval steps that slow response times. Establishing exception-based governance, where only high-risk or low-confidence outputs require human escalation, can help maintain speed and control.
3. Update policies and controls that restrict automation and data-driven decision-making. Many policies were written for manual processes and can unintentionally limit what digital tools can do (e.g., an outdated procurement policy that requires a three-bid comparison).
Roles and Upskilling
4. Conduct a role and task impact assessment to understand how new technologies will affect supply chain jobs at a detailed level.
5. Redesign roles and organizational structures to reflect the integration of digital technology, and help everyone understand their new responsibilities and decision-making responsibilities.
6. Develop targeted training programs that go beyond tool usage to emphasize digital collaboration, data literacy and informed decision-making.
Key Performance Indicators
7. Realign KPIs with the new systems. “Business and functional teams must work in collaboration with technology, data and analytics groups,” EY recommends, “to redefine KPIs aligned with the capabilities of new systems and the strategic goals of the transformation.”
8. Communicate the new expectations. As KPIs evolve to reflect digital tools and automated workflows, new areas of accountability (i.e., exception response time, data quality adherence or automation utilization rates) may emerge and need to be addressed.
9. Bring external partners onboard. “Modern supply chains operate within connected ecosystems of suppliers, logistics partners and customers,” says EY. “Key partners (e.g., suppliers, 3PLs, customers) must also understand and align to new metrics, especially where AI and automation are [being] introduced.”
